A conventional emergency medical service (EMS) system comprises, for example, a color video camera, a video decoding and compression device, a wireless transmitter, a wireless receiver, a video decompression and coding device, and a video monitor. More than in other public safety applications, it is imperative that video used for emergency medical service (EMS) applications retains color truth throughout the EMS system, for example, during recording of the video, transfer of the video, and display of the video. This is because any impairment of color information during the recording, the transferring, and/or display of the video can be life threatening as the color of, for example, blood, skin, etc., of a patient is often used to make critical diagnoses. Currently, transmission of the video over a network, for example, a mobile communication network, results in color distortion of the video due to presence of multiple distortion factors, for example, ineffective data compression algorithms, communication channels, inadequate display monitors, lighting conditions, etc., that cause impairments in the video. The distortion factors distort the color information in the video, which is critical to EMS applications. Hence, there is a need for a method and a system that correct color of an image of a patient while considering all the distortion factors that affect the color of the image of the patient.
Color correction of images has been studied for decades and efforts have been made for correcting colors of an image. For example, one of the conventional techniques for correcting color of an image involves capturing a photographic image of a color card that is positioned in a field of view of a camera. The captured photo image is then transferred to a computer. A user then needs to manually select and highlight the color card inside the photo image and run software to correct the color of the photo image. However, this technique allows color correction of only a single photo image and is ineffective for processing video in real time. Moreover, this technique does not include a display unit in the system and hence cannot automatically adjust gamma parameters on the display unit. The technique can only process a photo image and save the processed photo image for printing and thus cannot ensure that the displayed color of the processed photo image is the true color of the photo image. Hence, there is a need for a method and a system that correct color of images in real world video applications.
Another conventional technique performs color correction by attaching a color chart to a patient's skin and generating a color correction curve from the colors on the color chart. Another conventional technique performs color correction by registering a standard point and an object point on color spaces, and determining a mapping function for the conversion of the color spaces. Another conventional technique performs color correction by adjusting chromatic values in an active region of an image by defining an operation window and a target window. Another conventional technique performs color reproduction using a correction matrix for white balance and a transformation matrix for a light source, where the correction matrices are generated from an image input apparatus. Another conventional technique performs color correction by picking up specific source regions on source images using two cameras. The colors of the source regions are then used to decide the color set and correct the colors in similar ranges to the reference colors. A disadvantage of these conventional techniques used for color correction is the need for an interactive means to specify the source color and the target color. A second disadvantage is that the target reference color is typically chosen subjectively, which leads to randomness of the color correction result. Moreover, these conventional techniques compensate for the color distortion caused due to only lighting conditions.
Hence, there is a long felt but unresolved need for a method and a system that corrects color of an image impaired due to multiple distortion factors in real time applications.